Aberrant cerebral perfusion pattern in amnestic mild cognitive impairment and Parkinson's disease with mild cognitive impairment: a comparative arterial spin labeling study

Cognitive impairment in Parkinson's disease and other parkinsonian syndromes

In this narrative review, we address mild cognitive impairment, a frequent complication of Parkinson's disease (PD) and atypical parkinsonian disorders (APDs). Recent diagnostic criteria have blurred the lines between PD and dementia with Lewy bodies (DLB), particularly in the cognitive domain. Additionally, atypical parkinsonian syndromes like progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) often present with significant cognitive decline. Even multiple system atrophy (MSA) can be associated with cognitive impairment in some cases. Several biomarkers, including imaging techniques, such brain magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET), as well as pathological proteins either of the cerebrospinal fluid (CSF), such as Tau, amyloid beta, and synuclein, or of the serum, such as neurofilament light chain (Nfl) are more and more often utilized in the early differential diagnosis of APDs. The complex interplay between these conditions and the evolving understanding of their underlying pathologies highlight the need for further research to refine diagnostic criteria, possibly incorporate the new findings from the biomarker's field into the diagnostic criteria and develop targeted therapeutic strategies.

Innovative Multivariable Model Combining MRI Radiomics and Plasma Indexes Predicts Alzheimer's Disease Conversion: Evidence from a 2-Cohort Longitudinal Study

To explore the complementary relationship between magnetic resonance imaging (MRI) radiomic and plasma biomarkers in the early diagnosis and conversion prediction of Alzheimer's disease (AD), our study aims to develop an innovative multivariable prediction model that integrates those two for predicting conversion results in AD. This longitudinal multicentric cohort study included 2 independent cohorts: the Sino Longitudinal Study on Cognitive Decline (SILCODE) project and the Alzheimer Disease Neuroimaging Initiative (ADNI). We collected comprehensive assessments, MRI, plasma samples, and amyloid positron emission tomography data. A multivariable logistic regression analysis was applied to combine plasma and MRI radiomics biomarkers and generate a new composite indicator. The optimal model's performance and generalizability were assessed across populations in 2 cross-racial cohorts. A total of 897 subjects were included, including 635 from the SILCODE cohort (mean [SD] age, 64.93 [6.78] years; 343 [63%] female) and 262 from the ADNI cohort (mean [SD] age, 73.96 [7.06] years; 140 [53%] female). The area under the receiver operating characteristic curve of the optimal model was 0.9414 and 0.8979 in the training and validation dataset, respectively. A calibration analysis displayed excellent consistency between the prognosis and actual observation. The findings of the present study provide a valuable diagnostic tool for identifying at-risk individuals for AD and highlight the pivotal role of the radiomic biomarker. Importantly, built upon data-driven analyses commonly seen in previous radiomics studies, our research delves into AD pathology to further elucidate the underlying reasons behind the robust predictive performance of the MRI radiomic predictor.

Cerebral blood flow changes in maintenance hemodialysis patients with restless legs syndrome and their clinical significance:a cross-sectional case-control study

OBJECTIVE

Restless legs syndrome (RLS) stands as a prevalent neurological complication within maintenance hemodialysis (MHD) patients. However, the alterations in cerebral blood flow (CBF) among MHD-RLS patients remain uncharted. Through the utilization of the arterial spin labeling (ASL) technique, we evaluated the fluctuations in CBF within distinct brain regions and analyzed the risk factors for the development of RLS in MHD patients in the context of the clinic.

METHODS

Thirty-one MHD patients with concomitant RLS (MHD-RLS group) and thirty-one non-RLS patients matched based on age, gender, as well as cognitive function (MHD-nRLS group) were included. Through image preprocessing and data analysis, the changes in CBF values in distinct brain regions were obtained, and the CBF values of brain regions with substantial differences between the two groups were correlated with the RLS scores. Furthermore, the differences in baseline data were compared, and through the utilization of multifactorial logistic regression, the independent risk factors for the development of RLS were examined.

RESULTS

Compared with the MHD-nRLS group, the MHD-RLS group had increased CBF in the right superior temporal gyrus, reduced CBF in the right hippocampus, left middle frontal gyrus, inferior frontal gyrus of right triangle, middle frontal gyrus of left orbit, left precentral gyrus, and left precuneus. Only left precentral gyrus CBF were negatively correlated with RLS scores after correction for dialysis duration(r = -0.436, P = 0.016). Accordingly, multifactorial regression analysis by stepwise method yielded that the left precentral gyrus CBF values(OR: 0.968, 95%CI: 0.944-0.993, P = 0.012) remained an independent risk factor for RLS in MHD patients. In addition, the results showed that hemodialysis duration (OR: 1.055, 95%CI: 1.014-1.098, P = 0.008) and serum iron levels (OR: 0.685, 95%CI: 0.551-0.852, P = 0.001) were also risk factors for the development of RLS.

CONCLUSION

Patients afflicted with MHD-RLS exhibit alterations in CBF across several brain regions. Notably, the left precentral gyrus might serve as a pivotal region influencing the onset of RLS among MHD patients. Furthermore, extended hemodialysis duration and a relative insufficiency in serum iron levels independently contribute as risk factors for RLS development within the MHD patient population.

Abnormalities of cerebral blood flow and the regional brain function in Parkinson's disease: a systematic review and multimodal neuroimaging meta-analysis

Background

Parkinson's disease (PD) is a neurodegenerative disease with high incidence rate. Resting state functional magnetic resonance imaging (rs-fMRI), as a widely used method for studying neurodegenerative diseases, has not yet been combined with two important indicators, amplitude low-frequency fluctuation (ALFF) and cerebral blood flow (CBF), for standardized analysis of PD.

Methods

In this study, we used seed-based d-mapping and permutation of subject images (SDM-PSI) software to investigate the changes in ALFF and CBF of PD patients. After obtaining the regions of PD with changes in ALFF or CBF, we conducted a multimodal analysis to identify brain regions where ALFF and CBF changed together or could not synchronize.

Results

The final study included 31 eligible trials with 37 data sets. The main analysis results showed that the ALFF of the left striatum and left anterior thalamic projection decreased in PD patients, while the CBF of the right superior frontal gyrus decreased. However, the results of multimodal analysis suggested that there were no statistically significant brain regions. In addition, the decrease of ALFF in the left striatum and the decrease of CBF in the right superior frontal gyrus was correlated with the decrease in clinical cognitive scores.

Conclusion

PD patients had a series of spontaneous brain activity abnormalities, mainly involving brain regions related to the striatum-thalamic-cortex circuit, and related to the clinical manifestations of PD. Among them, the left striatum and right superior frontal gyrus are more closely related to cognition.

Systematic review registration

https://www.crd.york.ac.uk/ PROSPERO (CRD42023390914).

Predictability of inter-regional cerebral perfusion similarity on dopamine responsiveness and the moderation role of cognition in PD patients

BACKGROUND

Large heterogeneity can be found in dopamine responsiveness of patients with Parkinson's disease (PD). Instantly and objectively understanding dopamine responsiveness of patients may help clinical practice.

PURPOSE

This PD study explored the predictability of off-state inter-regional cerebral blood flow (CBF) perfusion similarity on patient's dopamine responsiveness and tested whether the predictive power could be moderated by patient's cognitive status.

MATERIALS AND METHOD

The PD cohort with 192 patients (containing off state and on state (PD-off and PD-on)) and the normal control (NC) cohort with 92 subjects were included. The intra-individual CBF relative variation networks were constructed and compared between PD-off and PD-on, PD-off and NC to identify the alterations caused by dopamine depletion. Based on that, regression analysis of off-state inter-regional CBF perfusion similarity on patient's dopamine responsiveness was performed. Finally, moderation analysis was conducted to test the moderation role of cognition on the regression model.

RESULTS

In the PD-off cohort, a total of 82 edges in the network were identified that affected by dopamine depletion. Off-state inter-regional CBF perfusion similarity was found that had a significant influence on patient's dopamine responsiveness. Cognitive status was validated that positively moderated the relationship between off-state inter-regional CBF perfusion similarity and dopamine responsiveness.

CONCLUSION

Dopamine responsiveness of PD patient could be predicted by off-state inter-regional CBF perfusion similarity. Patient's cognitive status might have a positive moderation effect on his/her dopamine responsiveness.

Role of Arterial Spin Labeling (ASL) Images in Parkinson's Disease (PD): A Systematic Review

RATIONALE AND OBJECTIVES

Parkinson's disease is a chronic progressive neurodegenerative disorder with standard structural MRIs often showing no gross abnormalities. Quantitative perfusion MRI modality Arterial Spin Labeling (ASL) is helpful in identifying PD specific perfusion patterns. Absolute Cerebral blood flow (CBF) measurement using ASL provides insights into regional perfusion abnormalities. We reviewed the role of ASL to identify specific brain regions responsible for motor, non-motor symptoms and neurovascular changes observed in PD. Challenges in assessing the blood perfusion level are discussed with future development for improving the evaluation of ASL perfusion maps.

MATERIALS AND METHODS

We included CBF quantification studies using ASL for PD diagnosis. A systematic search was performed in Pubmed, Scopus and Web of Science. The perfusion parameters CBF and arterial arrival time (AAT) measured using ASL were considered for brain region assessment. Clinical aspects of PD have been analyzed using ASL perfusion maps.

RESULTS

The systematic search identified 153 unique records. Thirty articles were selected after verification of inclusion and exclusion criteria. Voxel and region-based analyses in white and gray matter tissues have been performed to identify PD-specific perfusion patterns by reported articles. Predominant brain regions such as basal ganglia sub-regions, frontoparietal network, precuneus, occipital lobe, sensory motor area regions, visual network, which are associated with motor and non-motor symptoms in PD, were identified with CBF hypoperfusion, indicating neuronal loss and cerebrovascular dysfunction.

CONCLUSION

CBF and AAT values derived from ASL can potentially be used as biomarkers to discriminate PD from similar brain-related disorders.

Multivariate logistic regression analysis of clinical characteristics and risk factors of cognitive impairment after cerebral ischemic stroke: implications for clinical treatment

Background

Stroke ranks first among disease fatalities, and those who do survive stroke are prone to cognitive impairment. The aim of this study was to explore the clinical characteristics of post stroke cognitive impairment (PSCI) and the risk factors of PSCI using multivariate logistic regression.

Methods

January 2018 to January 2021, the clinical data of 120 patients treated for cerebral ischemic stroke (CIS) at Chengde Central Hospital were retrospectively analyzed. In this study, patients were divided into 2 groups: a control group and a cognitive impairment group. The clinical characteristics of cognitive impairment following CIS were determined using multivariate logistic regression analysis to examine the risk factors and identify clinical implications.

Results

This study included the assessment of overall cognitive function and daily living activities of 120 participants, 68 of whom experienced cognitive impairment, representing an incidence of 57%, while 43% patients represented no cognitive impairment after CIS. After the careful analysis of the data, there were remarkable differences in age, sex, education level, stroke history, infarction area, and infarction location (P<0.05). There was no remarkable difference in the history of hypertension, diabetes, atrial fibrillation, carotid intima thickness, smoking, or drinking (P>0.05). The degree of white matter degeneration, brain atrophy, and dominant hemisphere involvement was higher in the cognitive impairment group (P<0.05). The results of multivariate logistic regression analysis indicated that sex, age, education level, stroke history, infarction size, and infarction location were the main risk factors for cognitive impairment after CIS (P<0.05).

Conclusions

Patients with cognitive impairment after CIS have imaging features of white matter degeneration, brain atrophy, and involvement of dominant hemispheres. The results of multivariate logistic regression analysis indicated that sex, age, education level, stroke history, infarct size, and infarct location were main risk factors of cognitive impairment after CIS.

Functional differentiation of the dorsal striatum: a coordinate-based neuroimaging meta-analysis

Background

The dorsal striatum, a nucleus in the basal ganglia, plays a key role in the execution of cognitive functions in the human brain. Recent studies have focused on how the dorsal striatum participates in a single cognitive function, whereas the specific roles of the caudate and putamen in performing multiple cognitive functions remain unclear. In this paper we conducted a meta-analysis of the relevant neuroimaging literature to understand the roles of subregions of the dorsal striatum in performing different functions.

Methods

PubMed, Web of Science, and BrainMap Functional Database were searched to find original functional magnetic resonance imaging (fMRI) studies conducted on healthy adults under reward, memory, emotion, and decision-making tasks, and relevant screening criteria were formulated. Single task activation, contrast activation, and conjunction activation analyses were performed using the activation likelihood estimation (ALE) method for the coordinate-based meta-analysis to evaluate the differences and linkages.

Results

In all, 112 studies were included in this meta-analysis. Analysis revealed that, of the 4 single activation tasks, reward, memory, and emotion tasks all activated the putamen more, whereas decision-making tasks activated the caudate body. Contrast analysis showed that the caudate body played an important role in the 2 cooperative activation tasks, but conjunction activation results found that more peaks appeared in the caudate head.

Discussion

Different subregions of the caudate and putamen assume different roles in processing complex cognitive behaviors. Functional division of the dorsal striatum identified specific roles of 15 different subregions, reflecting differences and connections between the different subregions in performing different cognitive behaviors.

Aberrant pattern of regional cerebral blood flow in mild cognitive impairment: A meta-analysis of arterial spin labeling magnetic resonance imaging

In mild cognitive impairment (MCI), cognitive decline is associated with abnormal changes of cerebral blood flow (CBF). Arterial spin labeling magnetic resonance imaging (ASL-MRI) is an effective method for assessing regional cerebral blood flow (rCBF). However, the CBF estimated via ASL-MRI in MCI often differs between studies, and the consistency of CBF changes in MCI is unclear. In this study, 13 ASL-MRI studies with 495 MCI patients and 441 health controls were screened out from PubMed, Embase, Cochrane, Web of Science, Wanfang, and CNKI. An activation likelihood estimation (ALE) meta-analysis was performed to explore the brain regions with abnormal CBF in MCI. It showed that the decreased CBF in MCI was identified in the precuneus, inferior parietal lobule (IPL), superior occipital gyrus (SOG), middle temporal gyrus (MTG), and middle occipital gyrus (MOG), while the increased CBF in MCI was identified in the lentiform nucleus (LN) compared with healthy controls. The study characterized the abnormal pattern of regional CBF in MCI, which would promote our knowledge of MCI and might be used as a biomarker in clinic.

Evaluating white matter alterations in Parkinson's disease-related parkin S/N167 mutation carriers using tract-based spatial statistics

Background

Genetic susceptibility plays an important role in the pathogenesis of Parkinson’s disease (PD). parkin S/N167 mutations may increase the risk of PD and affect white matter fibers in the brain. This cross-sectional study explored the effects of gene polymorphisms on white matter fiber damage in PD.

Methods

In all, 54 cases were enrolled in the study, including PD patients carrying parkin gene S/N167 mutations (G/A), PD patients without gene S/N167 mutations (G/G), and healthy controls (HC). The whole-brain white matter fiber skeleton was analyzed using the tract-based spatial statistics (TBSS) method. Two-way analysis of variance (ANOVA) and post hoc tests were used for data analyses.

Results

Two classification methods were used; one was based on disease classification, with 26 patients in the PD group (n=12 G/G, n=14 G/A) and 28 in the HC group (n=15 G/G, n=13 G/A), and the other was based on genetic classification, with 27 patients in the G/G group and 27 in the G/A group. In the G/A group, there was a wide range of significant changes in fractional anisotropy (FA), radial diffusivity (RD), and mean diffusivity (MD) values (P<0.05). There was also a significant decrease in FA in the PD-G/A group compared with the PD-G/G and HC-G/A groups (P<0.05).

Conclusions

There were more extensive brain white matter fiber damage and changes in PD patients; the G/A polymorphism may cause more extensive brain white matter damage.

White matter damage in patients with mild cognitive impairment in Parkinson's disease

BACKGROUND

This study investigates the correlation between white matter structural damage and cognitive impairment in patients with Parkinson's disease (PD) and mild cognitive impairment (MCI).

METHODS

A total of 40 patients with PD were divided into two groups, i.e., a mild cognitive impairment (PD-MCI) and a normal cognitive (PDN) group, and 20 healthy patients were enrolled as the control group. Changes in the white matter structure of patients with PD were evaluated using diffusion tensor imaging (DTI), and cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA) scale and Mini-Mental State Examination (MMSE). Finally, the correlations between the two groups were analyzed.

RESULTS

The Unified Parkinson's Disease Rating Scale score was significantly higher in the PD-MCI than in the PDN group (P=0.008). The total MoCA and MMSE scores in the PD-MCI group were significantly lower than in the PDN and control groups (P<0.01). Patients in PDMCI group were tested by MMSE scale, and the abnormal score rate was 60.0%. Among them, 8 PD patients with normal MMSE total score were found to have mild cognitive impairment by MoCA evaluation. When compared with the PDN and control groups, the MoCA scores for visual space, which is assessed as part of the MoCA scale and generally represents bilateral parietal function; naming; memory; and attention were significantly lower in the PD-MCI group (P<0.001). When compared with the PDN group, the fractional anisotropy (FA) values for the right parietal and left occipital lobes were significantly lower in the PD-MCI group (P=0.005; P=0.018). The relationship between MoCA value and right parietal white matter and left occipital white matter was 0.555, 0.474, respectively. A Pearson's correlation test was conducted to compare the FA values and MoCA scores of the various brain areas in the PD-MCI group and revealed a significant positive correlation between the MoCA score and the white matter of the right parietal and left occipital lobes (P<0.01).

CONCLUSIONS

Patients with PD experience early cognitive impairment, and the MoCA scale can be used for early screening. In addition, the DTI of white matter can highlight early white matter damage. In the current study, the damaged brain areas displayed by DTI were consistent with areas showing decreased MoCA scores and were positively correlated with the severity of PD.